Model analysis and experiment study for effects of thermal viscous and fluid flow on ventilated acoustic metamaterials labyrinth by Shengnan Du, Dacheng Zhang, Xianming Sun, Xiaoping Chen, Guowei Zhang

“…The theoretical results are compared with the experimental results with an error of 0.6%. By comparing the transmission coefficient and the impedance at the entrance of the side branches, the mechanism of the TVE on the performance of VAML is analyzed, and it is clarified that the TVE is responsible for the sound absorption coefficient. …”
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EFFECTS OF MACRO-ECONOMIC VARIABLES ON FISHERIES SUPPLY IN NIGERIA (1980-2019) by Ahmed Olugbenga BUSARI, Abolupe Oluyemi AYANBOYE

“…Thus, it is recommended that there is a need for significant improvement in aquaculture production and reduction in fish importation to cushion the effect of exchange, inflation, and interest rate on the economy.…”
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Adaptive fractal dynamics: a time-varying Hurst approach to volatility modeling in equity markets by Abe Webb, Siddharth Mahajan, Mateo Sandhu, Rohan Agarwal, Arjun Velan

“…Additionally, the model achieves an average absolute option pricing error of 1.8 %, markedly lower than that of traditional specifications. …”
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Extreme heat prediction through deep learning and explainable AI. by Fatima Shafiq, Amna Zafar, Muhammad Usman Ghani Khan, Sajid Iqbal, Abdulmohsen Saud Albesher, Muhammad Nabeel Asghar

“…Making these models understood allows us to identify important parameters, improving heatwave forecasting accuracy and guiding risk-reduction strategies.…”
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Transforming higher education with robotic process automation: enhancing efficiency, innovation, and student-centered learning by Vivek Bhardwaj, Mukesh Kumar

“…Case studies reveal common success factors, including significant time savings, error reduction, and improved satisfaction for both students and staff. …”
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A Data-Driven Approach for Energy Consumption Modeling and Optimization of Welding Robot Systems by Minling Pan, Bingqi Jia, Lei Zhang, Haihong Pan, Lin Chen

“…A predictive model was developed using an extreme gradient boosting (XGBoost) regression technique focused on joint torque data, which achieved a mean absolute percentage error (MAPE) of 1.86%. Furthermore, trajectory optimization was achieved by adjusting the spatial position of the workpiece, effectively reducing EC. …”
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Comparative Evaluation of Preprocessing Methods for MobileNetV1 and V2 in Waste Classification by Aulia Afifah, Endah Ratna Arumi, Maimunah Maimunah, Setiya Nugroho

“…Overall, MobileNetV1 benefited more significantly from preprocessing variations than MobileNetV2, particularly in terms of accuracy improvement and reduction in prediction error. These findings underscore the importance of effective preprocessing in enhancing model performance for waste image classification…”
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Big data-driven corporate financial forecasting and decision support: a study of CNN-LSTM machine learning models by Aixiang Yang

“…The data underwent preprocessing and dimensionality reduction via Principal Component Analysis (PCA) to eliminate redundancy and noise. …”
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Earthwork Network Architecture (ENA): Research for Earthwork Quantity Estimation Method Improvement with Large Language Model by Taewook Kang, Kyubyung Kang

“…Traditional methods for quantity takeoff are often time-consuming and susceptible to human error, particularly when working with unstructured datasets such as CAD drawings. …”
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Study on the effect of humidity on coal mine dust concentration monitoring and its compensation strategy by ZHANG Anran

“…Results showed that the monitoring error of the humidity-compensated multi-angle light-scattering unit was ≤11.2%, a 2.9% reduction compared to the uncompensated unit, confirming the effectiveness of the compensation method.…”
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High-normal blood glucose levels may be associated with decreased spatial perception in young healthy adults. by Rima Abdul Razzak, Abdulla Faisal Alshaiji, Abdulrahman Ahmed Qareeballa, Mohamed Wael Mohamed, Jeff Bagust, Sharon Docherty

“…Linear regression analysis showed that blood glucose level at testing correlated positively with all alignment spatial error parameters, indicating a probable reduction of spatial perception ability with higher blood glucose levels. …”
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A targeted one dimensional fully convolutional autoencoder network for intelligent compression of magnetic flux leakage data by Wenbo Xuan, Pengchao Chen, Rui Li, Fuxiang Wang, Kuan Fu, Zhitao Wen

“…Through practical experimental analysis, the reconstruction error such as MAE is reduced by about 27.7% and the compression ratio is improved by about 14% compared with traditional methods such as PCA. …”
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Zero-Offset VSP Monitoring of CO2 Storage: Impedance Inversion and Wedge Modelling at the Ketzin Pilot Site by Julia Götz, Stefan Lüth, Charlotte M. Krawczyk, Calin Cosma

“…With band limited impedance inversion a velocity reduction at the top of the reservoir of 30%, influenced by casing reverberations as well as CO2 injection, is found. …”
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Influence of Rice Husk Ash on Crystalline Phases and Mechanical Characteristics of Sustainable Bricks by F. Booth, M.B. Carranza, G. Novak, N. Okulik, A. Mocciaro, N. Rendtorff

“…Theoretical models, such as the DEM, proved effective in describing how porosity influences mechanical properties, particularly elastic modulus and modulus of rupture. Despite the reduction in mechanical properties, bricks with up to 15% RHA are suitable for non-structural applications, offering an eco-friendly alternative to conventional bricks. …”
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Intelligent Noise Removal from EMG Signal Using Focused Time-Lagged Recurrent Neural Network by S. N. Kale, S. V. Dudul

“…ANN approach is studied for reduction of noise in EMG signal. In this paper, it is shown that Focused Time-Lagged Recurrent Neural Network (FTLRNN) can elegantly solve to reduce the noise from EMG signal. …”
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Time-Series Interval Forecasting with Dual-Output Monte Carlo Dropout: A Case Study on Durian Exports by Unyamanee Kummaraka, Patchanok Srisuradetchai

“…The dual-output architecture employs a custom loss function, combining mean squared error with Softplus-derived predictive variance, ensuring non-negative variance values. …”
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Improved Remote Photoplethysmography Using Machine Learning-Based Filter Bank by Jukyung Lee, Hyosung Joo, Jihwan Woo

“…In this study, we propose a machine learning-based filter bank (MLFB) noise reduction algorithm to improve the quality of rPPG signals. …”
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Towards an Explainable Artificial Intelligence approach for smart grid systems by Mahmoud Alfayan, Hani Hagras

“…The transition from a Type-1 to a Type-2 fuzzy logic system resulted in enhanced prediction performance, as evidenced by a reduction in the root mean square error (RMSE) from 8.7734 to 5.9422, resulting in 32.2% enhancement in RMSE. …”
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Multimodal fusion for athlete state prediction leveraging XLNet and deep generative models by Yafeng Feng, Yong Sun, Chengfang Hang

“…Experimental results show that our model achieves a significant improvement in classification accuracy, with a 12% increase in emotional state recognition compared to traditional models, and a 15% reduction in prediction error for physiological state estimation. …”
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Hybrid Spectrum Sensing Using Neural Network–Based MF and ED for Enhanced Detection in Rayleigh Channel by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…Furthermore, the capability of the NN to mitigate noise and interference results in enhanced bit error rate (BER) performance, ensuring reliable communication. …”
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